Journal of Logic, Language and Information

, Volume 14, Issue 1, pp 1–12 | Cite as

Local Logics, Non-Monotonicity and Defeasible Argumentation

  • Gustavo A. Bodanza
  • Fernando A. Tohmé


In this paper we present an embedding of abstract argumentation systems into the framework of Barwise and Seligman’s logic of information flow. We show that, taking P.M. Dung’s characterization of argument systems, a local logic over states of a deliberation may be constructed. In this structure, the key feature of non-monotonicity of commonsense reasoning obtains as the transition from one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions of argument systems leads to a corresponding ordering of background conditions. The relations among extensions becomes a relation among partial orderings of background conditions. This introduces a conceptual innovation in Barwise and Seligman’s representation of commonsense reasoning.


Defeasible argumentation local logics non-monotonicity 


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  1. Barwise, J., 1999, “State spaces, local logics and non-monotonicity,” in Logic, Language and Computation, Vol. 2, L. Moss, J. Ginzburg, and M. de Rijke, eds., Stanford: CSLI Publications.Google Scholar
  2. Barwise, J. and Seligman, J., 1997, Information Flow: The Logic of Distributed Systems, Cambridge, MA: Cambridge University Press.Google Scholar
  3. Dung, P.M., 1995, “On the acceptability of arguments and its fundamental role in non-monotonic reasoning, logic programming, and n-person games,” Artificial Intelligence 77, 321–357.Google Scholar
  4. McCarthy, J., 1980, “Circumscription – A form of non-monotonic reasoning,” Artificial Intelligence 13, 27–39.Google Scholar
  5. McCarthy, J. and Hayes, P., 1969, “Some philosophical problems from the standpoint of artificial intelligence,” in Machine Intelligence 4, B. Meltzer and D. Mitchie, eds., Edimburg University Press.Google Scholar
  6. McDermmot, J. and Doyle, J., 1980, “Non-monotonic Logic I,” Artificial Intelligence 13, 41–72.Google Scholar
  7. Lin, F. and Shoham, Y., 1989, “Argument systems: a uniform basis for nonmonotonic reasoning,” pp. 245–255 in Proceedings of the 1st International Conference on Knowledge Representation and Reasoning, San Mateo, CA: Morgan Kaufmann Publishers.Google Scholar
  8. Loui, R., 1987, “Defeat among arguments: a system of defeasible inference,” Computational Intelligence 3, 100–106.Google Scholar
  9. Loui, R., 1998, “Process and policy: resource-bounded non-demonstrative reasoning,” Computational Intelligence 14, 1–38.Google Scholar
  10. Pollock, J., 1987, “Defeasible reasoning,” Cognitive Science 11, 481–518.Google Scholar
  11. Poole, D., 1988, “A logical framework for default reasoning,” Artificial Intelligence 36, 27–47.Google Scholar
  12. Reiter, R., 1980, “A logic for default reasoning,” Artificial Intelligence 13, 81–132.Google Scholar
  13. Simari, G. and R. Loui, 1992 “A mathematical treatment of defeasible reasoning and its implementation,” Artificial Intelligence 53, 125–157.Google Scholar

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Departamento de HumanidadesUniversidad Nacional del Sur8000 Bahía BlancaArgentina
  2. 2.Departamento de EconomíaUniversidad Nacional del Sur8000 Bahía BlancaArgentina

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